On the largest eigenvalue of a Hermitian random matrix model with spiked external source II. Higher rank cases

TL;DR

This paper extends the analysis of the largest eigenvalue distribution in Hermitian random matrices with spiked external sources to higher rank cases, revealing phase transitions and universal fluctuation laws.

Contribution

It generalizes previous work from rank-one to higher rank external sources, analyzing phase transitions and eigenvalue behavior for convex and non-convex potentials.

Findings

Eigenvalues below critical value converge to support endpoint

Eigenvalues above critical value are pulled off the support

Discontinuous transitions occur in non-convex potentials

Abstract

This is the second part of a study of the limiting distributions of the top eigenvalues of a Hermitian matrix model with spiked external source under a general external potential. The case when the external source is of rank one was analyzed in an earlier paper. In the present paper we extend the analysis to the higher rank case. If all the eigenvalues of the external source are less than a critical value, the largest eigenvalue converges to the right end-point of the support of the equilibrium measure as in the case when there is no external source. On the other hand, if an external source eigenvalue is larger than the critical value, then an eigenvalue is pulled off from the support of the equilibrium measure. This transition is continuous, and is universal, including the fluctuation laws, for convex potentials. For non-convex potentials, two types of discontinuous transitions are possible to occur generically. We evaluate the limiting distributions in each case for general potentials including those whose equilibrium measure have multiple intervals for their support.